In connection with economic analyses of development projects and policies, valuation research has been conducted in Armenia on water resources protection, in Thailand on transportation, in India on water supply and non-motor transport, and in China on water supply, urban solid wastes, water resources protection, and public health.

In determining domestic water prices, policy makers often need to use information about the demand side rather than only relying on information about the supply side. Household surveys have frequently been employed to collect demand-side information. This paper presents a multiple bounded discrete choice household survey model. It discusses how the model can be utilized to collect and analyze information about the acceptability of different water prices by different types of households, as well as households' willingness to pay for water service improvement. The results obtained from these surveys can be directly utilized in the development of water pricing and subsidy policies. The paper also presents an empirical multiple bounded discrete choice study conducted in Chongqing, China. In this case, domestic water service quality was seriously inadequate, but financial resources were insufficient to improve service quality. With a survey of about 1,500 households in five suburban districts in Chongqing Municipality, this study shows that a significant increase in the water price is feasible as long as the poorest households can be properly subsidized and certain public awareness and accountability campaigns can be conducted to make the price increase more acceptable to the public. The analysis also indicates that the order in which hypothetical prices are presented to respondents systematically affects their answers, and should be taken into account when designing survey instruments.

This paper presents a case study of willingness-to-pay (WTP) estimation using random valuation models. A contingent valuation survey was conducted in Yerevan, Armenia to estimate people's WTP for the protection of Lake Sevan. Three elicitation formats-open-ended, closed-ended, and the stochastic payment card (SPC) approach-were used with split random samples. WTP models with heterogeneous errors were constructed and estimated with the survey data. The SPC approach produces a higher estimation of the mean WTP than both the open-ended and closed-ended approaches, while results from the open-ended and closed-ended elicitation formats are similar. Furthermore, contrary to research findings obtained in the United States, this study finds higher WTP estimations with mail surveys than with personal interviews.

The authors use a contingent valuation method to study the design of economic incentives to phase out polluting motorcycles in Bangkok. Like in many other cities, the government of Bangkok has been considering a series of control measures to discourage and eventually eliminate the use of heavily polluting motorcycles. Two of the possible policy instruments under consideration are charges on those polluting vehicles which are operating in the streets and compensation to those polluting vehicles which would stay off the roads. The policy research questions then include (1) what are the charges implied or compensation provided, given a policy target, and (2) what are the reactions of motorcycle owners to those charges or compensation. To answer those policy questions, the authors conducted a stochastic contingent valuation survey in Bangkok to question motorcycle owners on the likelihood they would keep or give up riding their motorcycles in the streets given certain charges or compensations. Results show that among others, about 80 percent of those motorcycles which did not pass the emission tests would be off the streets if a charge of 1,000 baht a year was levied, while under a one-time compensation of 10,000 baht, the number would be about 50 percent. The authors also estimate the average values of maximum willingness to pay (WTP) for staying on the road and minimum willingness to accept (WTA) compensation for staying off the street, and analyze the determinants of WTP and WTA. Their econometric analysis shows that, among other factors, household income, fuel costs, use of motorcycles, and/or public transit affect the value of WTP and WTA.